Zebrafish Diet and Infection Targetted Analysis
Connor Draney, Sunni Patton, Kelly Shannon, Michael Sieler
05 March, 2022
1 Import Data
We obtained data in the form of a phyloseq data object from the Human Genome Project (HMP) that was previously processed for taxanomic identification of microbial organisms. We then cleaned and processed the data further for statistical analysis.
# Download Data
# temp_test = tempfile()
# test_url = "http://joey711.github.io/phyloseq-demo/HMPv35.RData"
# download.file(test_url, destfile = paste0(data.path, "/Raw/HMPv35.RData"))
load(paste0(data.path, "/Raw/HMPv35.RData"))
ps.unclean <- HMPv35
rm(HMPv35) # remove this obj from global env1.1 Clean sample data
The 4743 samples in the HMP were obtained from multiple individuals (2555 males and 2188 females), processed by several locations, and in some cases repeated samples were taken from the same individual. We subset the data to ensure independence by limiting samples from one location and only the first visit. Additionally, we removed samples noted as “Mislabeled” or “Contaminated”. After removing samples using these criteria, we were left with 609 samples.
# Find the center with largest counts for the following conditions
sample.data.frame(ps.unclean) %>%
count(RUNCENTER,
Mislabeled,
Contaminated,
visitno) %>%
arrange(-n)## RUNCENTER Mislabeled Contaminated visitno n
## 1 JCVI FALSE FALSE 1 609
## 2 BCM FALSE FALSE 2 583
## 3 BI FALSE FALSE 1 538
## 4 WUGC FALSE FALSE 1 518
## 5 WUGC NA NA 1 513
## 6 WUGC FALSE FALSE 2 473
## 7 JCVI FALSE FALSE 2 400
## 8 BI FALSE FALSE 2 380
## 9 BI NA NA 1 160
## 10 BCM,BI NA NA 1 85
## 11 JCVI,WUGC NA NA 1 79
## 12 JCVI,BI NA NA 1 75
## 13 BCM FALSE FALSE 1 73
## 14 BCM,WUGC FALSE FALSE 1 49
## 15 BCM,WUGC NA NA 1 41
## 16 WUGC NA NA 2 26
## 17 BCM NA NA 1 25
## 18 BCM,JCVI FALSE FALSE 1 23
## 19 BCM,JCVI FALSE FALSE 2 17
## 20 BCM FALSE FALSE 3 15
## 21 JCVI,WUGC FALSE FALSE 1 14
## 22 BCM,BI FALSE FALSE 2 12
## 23 WUGC FALSE FALSE 3 9
## 24 BI,BCM NA NA 1 7
## 25 BCM,BI FALSE FALSE 1 6
## 26 BI,BCM FALSE FALSE 2 6
## 27 WUGC,BCM FALSE FALSE 1 5
## 28 WUGC,BCM NA NA 1 1
## 29 WUGC,JCVI NA NA 1 1# Subset based on parameters
ps.cleaned <- subset_samples(ps.unclean, # physeq object
Mislabeled == F & # Remove mislabeled
Contaminated == F & # remove contaminated
visitno == 1 & # first visit, so no repeat sampling of individuals, independence
RUNCENTER == "JCVI" # Same center, independence
)
# Remove columns, if rownames are already sample names, no need to have an extra sample column
sample_data(ps.cleaned) <- sample_data(ps.cleaned)[, c(-1)] # [rows, cols]
# Check to see how many samples dropped from original dataset
print(paste0("Dropped ",
nrow(sample_data(ps.unclean)) - nrow(sample_data(ps.cleaned)),
" samples after cleaning.")
)## [1] "Dropped 4134 samples after cleaning."2 Rarefaction
We rarefied the data to control for uneven sampling efforts Sanders, H. L. (1968), Willis, A.D. (2019).
ps.norm <- ps.cleaned
rarefaction.minimum <- 1000
min.smpl.size <- min(sample_sums(ps.norm)[sample_sums(ps.norm) >= rarefaction.minimum])
summary(sample_sums(ps.norm))## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1 2679 3577 3863 4696 29969# Rarefy
ps.rar <- {
ps.rar.tmp0 <- ps.norm
ps.rar.tmp1 <- rarefy_even_depth(
physeq = ps.rar.tmp0,
sample.size = min.smpl.size,
trimOTUs = TRUE,
rngseed = 42
)
rename.NA.taxa(ps.rar.tmp1)
}
ps.rar## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 24839 taxa and 562 samples ]
## sample_data() Sample Data: [ 562 samples by 8 sample variables ]
## tax_table() Taxonomy Table: [ 24839 taxa by 7 taxonomic ranks ]
## phy_tree() Phylogenetic Tree: [ 24839 tips and 24650 internal nodes ]
## refseq() DNAStringSet: [ 24839 reference sequences ]3 Plot pre- and post-rarefaction
Check the number of reads before and after rarefaction.
# rare.plot.preRare <- rarecurve(t(otu_table(ps.norm)), step=50, cex=0.5, label=F)
hist(sample_sums(ps.norm), main="Histogram: Read Counts before rarefaction", xlab="Total Reads",
border="blue", col="green", las=1, breaks=12)
hist(sample_sums(ps.rar), main="Histogram: Read Counts after rarefaction", xlab="Total Reads",
border="blue", col="green", las=1, breaks=12)
# Make a list of phyloseq objects, dataframes and datatables
ps.list <- list(RAR = list(ps.all = ps.rar,
df.all = sample.data.frame(ps.rar),
dt.all = sample.data.table(ps.rar)
))
# Add observation numbers to data
ps.list[["RAR"]][["df.all"]] <- dplyr::mutate(ps.list[["RAR"]][["df.all"]], obs_num = row_number(), .before = 1)
ps.list[["RAR"]][["dt.all"]] <- dplyr::mutate(ps.list[["RAR"]][["dt.all"]], obs_num = row_number(), .before = 1)
# head(ps.list$RAR$df.all)4 Alpha-diversity
We calculated alpha diversity scores, a measure of number of unique organisms within a single sample, using the indices Shannon, Simpson, Phylogenetic, and Richness (Whittaker 1960). Each calculates alpha-diversity using slightly different mathematical approaches to measure evenness (distribution of organisms) and/or richness (number of organismss). If differences in results are seen between indices, this can reveal insights into which kinds of organisms are present (e.g., common vs rare).
# Select which alpha measures we want to analyze
methods.alpha <- c("Shannon", "Simpson", # Non-phylogenetic measures, add additional measures here
"Phylogenetic", "Richness") %>%
purrr::set_names() # Set's names list elements in "alpha.methods"
# Calculate alpha scores, save to list
ps.list$RAR[["alphaScore"]] <- alpha_base(ps.list$RAR$ps.all, # Phyloseq object
methods.alpha, # list of alpha methods
"Sample",
phylo.div = T
)## [1] "Calculating non-phylogenetic alpha scores..."## Warning in `[.data.table`(tmp.dt, , `:=`(se.chao1, NULL)): Column 'se.chao1'
## does not exist to remove## [1] "Calculating phylogenetic alpha scores..."# Add alpha scores to data table
ps.list$RAR[["dt.all.alpha"]] <- ps.list$RAR$dt.all[ps.list$RAR$alpha, on = "Sample"] %>% setkeyv("Sample")
# Melt data table
ps.list$RAR[["dt.all.alpha.melt"]] <- melt_to_datatable_2(datatable1 = ps.list$RAR$dt.all,
datatable2 = ps.list$RAR$dt.all.alpha,
vars = methods.alpha,
var.name = "Alpha.Metric",
samp.name = "Sample",
val.name = "Alpha.Score"
)5 Fit linear model
We fit the data using linear model to predict alpha-diversity score as a function of body sub-site, sex, or their interaction.
caseInfStats <- list()
data <- ps.list$RAR[["dt.all.alpha.melt"]]
# data <- dplyr::mutate(data, obs_num = row_number(), .before = 1)
caseInfStats[["mod.unref"]] <- lapply(methods.alpha, function(alpha){
lm( formula = "Alpha.Score ~ sex*HMPbodysubsite",
data = subset(data, Alpha.Metric == alpha)
)
})5.1 Check assumptions
To assess if the assumptions of linear model regression were met, we visually inspected residuals vs fitted values, standardized residuals vs quantiles, standardized residuals vs fitted values and residuals vs leverage for each diversity index. In general, Residuals vs fitted appears slightly heteroscedasticity, Q-Q plots show that the data slightly deviates from the diagonal line indicating that the data may be non-normal, Scale-location plots show that std. residuals are negatively associated with fitted values indicating heteroscedasticity, and there are several points with high leverage, but none that appear to have too high. The plots associated with the Simpson’s index appear to be significantly heteroscedastic and non-normal.
5.1.1 Shannon
index <- "Shannon"
plot(caseInfStats[["mod.unref"]][[index]], sub = paste0("(Unrefined: ", methods.alpha[index],")") )## Warning: not plotting observations with leverage one:
## 234
5.1.2 Simpson
index <- "Simpson"
plot(caseInfStats[["mod.unref"]][[index]], sub = paste0("(Unrefined: ", methods.alpha[index],")") )## Warning: not plotting observations with leverage one:
## 234
5.1.3 Phylogenetic
index <- "Phylogenetic"
plot(caseInfStats[["mod.unref"]][[index]], sub = paste0("(Unrefined: ", methods.alpha[index],")") )## Warning: not plotting observations with leverage one:
## 234
5.1.4 Richness
index <- "Richness"
plot(caseInfStats[["mod.unref"]][[index]], sub = paste0("(Unrefined: ", methods.alpha[index],")") )## Warning: not plotting observations with leverage one:
## 234
6 Remove unusual observations
The previous plots revealed that the data is largely consistent, but there are some inconsistencies in variance and non-normality for some of the alpha indices. To correct for this, we applied case influence statistics to remove any unusually influential and leveraged samples. We removed any samples using cutoffs of 2p/n (p is the number of unknown parameters in the model) for leverage, 1 for Cook’s Distance and above 2 or below -2 for standardized residuals.
caseInfStats <- list()
data <- ps.list$RAR[["dt.all.alpha.melt"]]
# data <- dplyr::mutate(data, obs_num = row_number(), .before = 1)
caseInfStats[["mod.unref"]] <- lapply(methods.alpha, function(alpha){
lm( formula = "Alpha.Score ~ sex*HMPbodysubsite",
data = subset(data, Alpha.Metric == alpha)
)
})
# Fortify data for plotting
caseInfStats[["dataFort.unref"]] <- lapply(methods.alpha, function(alpha){
fortify(caseInfStats$mod.unref[[alpha]], subset(data, Alpha.Metric == alpha))
})
# Rename some column names
lapply(methods.alpha, function(alpha){
setnames(caseInfStats$dataFort.unref[[alpha]],
old=c(".hat", ".cooksd", ".stdresid"),
new=c("Lev", "CooksD", "StdResid"))
})
# Unrefinded model
## Plot
caseInfStats[["unref.plot"]] <- lapply(names(methods.alpha), function(alpha){
qplot(obs_num, value, data = reshape::melt(caseInfStats$dataFort.unref[[alpha]][, c("obs_num","Lev", "CooksD", "StdResid")],
id.vars = "obs_num")) +
geom_point(aes(color = variable)) +
facet_grid(variable ~ ., scale = "free_y") +
labs(title = paste0("Case-influence statistics plot: Unrefined model (", alpha,")")) +
scale_color_brewer(palette = "Dark2") +
theme(legend.position = "none") + scale_x_continuous(breaks = scales::breaks_pretty(10))
})
names(caseInfStats[["unref.plot"]]) <- names(methods.alpha)From the original 562 samples, we removed 45, 54, 33, and 31 unusual observations in the Shannon, Simpson, Phylogenetic and Richness indices, respectively.
7 Fit refined model
After removing the unusual samples, we refit the data to a linear model.
# Refined model
### Statisticians use rough cutoffs of 2p/n (p is the number of unknown parameters in the model) for leverage,
# 1 for Cook’s Distance and above 2 or below -2 for standardized residuals.
# Observations falling outside these ranges warrant further attention.
caseInfStats[["cutoff.lev"]] <- lapply(methods.alpha, function(alpha){
cutOff.lev <- (2 * length(caseInfStats$mod.unref[[alpha]][["coefficients"]]) /
nrow(caseInfStats$dataFort.unref[[alpha]]))
})
caseInfStats[["dataFort.sub"]] <- lapply(methods.alpha, function(alpha){
caseInfStats$dataFort.unref[[alpha]] %>%
dplyr::filter(Lev < caseInfStats[["cutoff.lev"]][[alpha]]) %>% # Leverage Cut off
dplyr::filter(StdResid < 2 & StdResid > -2 ) %>% # StdResid Cut Off
dplyr::select(obs_num:Alpha.Score) # Removes the old case statistic influence data
})
# make refined model
caseInfStats[["mod.ref"]] <- lapply(methods.alpha, function(alpha){
lm( formula = "Alpha.Score ~ sex*HMPbodysubsite",
data = caseInfStats[["dataFort.sub"]][[alpha]]
)
})
# Fortify data for plotting
caseInfStats[["dataFort.ref"]] <- lapply(methods.alpha, function(alpha){
fortify(caseInfStats$mod.ref[[alpha]], caseInfStats[["dataFort.sub"]][[alpha]])
})
# Rename some column names
lapply(methods.alpha, function(alpha){
setnames(caseInfStats$dataFort.ref[[alpha]],
old=c(".hat", ".cooksd", ".stdresid"),
new=c("Lev", "CooksD", "StdResid"))
})
# Refinded model Plot
caseInfStats[["ref.plot"]] <- lapply(names(methods.alpha), function(alpha){
tmp.data <- caseInfStats[["dataFort.ref"]]
qplot(obs_num, value, data = reshape::melt(tmp.data[[alpha]][, c("obs_num","Lev", "CooksD", "StdResid")],
id.vars = "obs_num")) +
geom_point(aes(color = variable)) +
facet_grid(variable ~ ., scale = "free_y") +
labs(title = paste0("Case-influence statistics plot: Refined model (", alpha,")")) +
scale_color_brewer(palette = "Dark2") +
theme(legend.position = "none") + scale_x_continuous(breaks = scales::breaks_pretty(10))
})
names(caseInfStats[["ref.plot"]]) <- names(methods.alpha)7.1 Linear Model Plots (refined)
After removing the unusual observations, the plots for each indice appear to have been improved. However, the Simpson’s data appears to not meet the assumptions of normality.
7.1.1 Shannon
index <- "Shannon"
plot(caseInfStats[["mod.ref"]][[index]], sub = paste0("(Refined: ", methods.alpha[index],")") )
7.1.2 Simpson
index <- "Simpson"
plot(caseInfStats[["mod.ref"]][[index]], sub = paste0("(Refined: ", methods.alpha[index],")") )
7.2 Plot unrefined and refined models
## $Shannon
##
## $Simpson
##
## $Phylogenetic
##
## $Richness
8 Results of linear model
8.1 Shannon
## Anova Table (Type II tests)
##
## Response: Alpha.Score
## Sum Sq Df F value Pr(>F)
## sex 2.139 1 12.3088 0.0004925 ***
## HMPbodysubsite 252.107 15 96.7150 < 2.2e-16 ***
## sex:HMPbodysubsite 5.719 12 2.7425 0.0013018 **
## Residuals 84.804 488
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## We fitted a linear model (estimated using OLS) to predict Alpha.Score with sex and HMPbodysubsite (formula: Alpha.Score ~ sex * HMPbodysubsite). The model explains a statistically significant and substantial proportion of variance (R2 = 0.77, F(28, 488) = 57.88, p < .001, adj. R2 = 0.76). The model's intercept, corresponding to sex = female and HMPbodysubsite = Anterior_nares, is at 4.52 (95% CI [4.28, 4.77], t(488) = 36.00, p < .001). Within this model:
##
## - The effect of sex [male] is statistically non-significant and positive (beta = 0.05, 95% CI [-0.29, 0.38], t(488) = 0.26, p = 0.792; Std. beta = 0.05, 95% CI [-0.34, 0.45])
## - The effect of HMPbodysubsite [Attached Keratinized gingiva] is statistically significant and negative (beta = -0.51, 95% CI [-0.82, -0.20], t(488) = -3.25, p = 0.001; Std. beta = -0.60, 95% CI [-0.97, -0.24])
## - The effect of HMPbodysubsite [Buccal mucosa] is statistically significant and negative (beta = -0.52, 95% CI [-0.85, -0.19], t(488) = -3.14, p = 0.002; Std. beta = -0.62, 95% CI [-1.00, -0.23])
## - The effect of HMPbodysubsite [Hard palate] is statistically non-significant and negative (beta = -0.16, 95% CI [-0.47, 0.16], t(488) = -0.98, p = 0.326; Std. beta = -0.19, 95% CI [-0.56, 0.19])
## - The effect of HMPbodysubsite [Left Retroauricular crease] is statistically significant and negative (beta = -0.95, 95% CI [-1.28, -0.62], t(488) = -5.64, p < .001; Std. beta = -1.12, 95% CI [-1.52, -0.73])
## - The effect of HMPbodysubsite [Mid vagina] is statistically significant and negative (beta = -1.11, 95% CI [-1.43, -0.79], t(488) = -6.88, p < .001; Std. beta = -1.32, 95% CI [-1.69, -0.94])
## - The effect of HMPbodysubsite [Palatine Tonsils] is statistically significant and positive (beta = 0.61, 95% CI [0.31, 0.91], t(488) = 3.97, p < .001; Std. beta = 0.72, 95% CI [0.36, 1.08])
## - The effect of HMPbodysubsite [Posterior fornix] is statistically significant and negative (beta = -1.43, 95% CI [-1.75, -1.11], t(488) = -8.78, p < .001; Std. beta = -1.70, 95% CI [-2.08, -1.32])
## - The effect of HMPbodysubsite [Right Retroauricular crease] is statistically significant and negative (beta = -0.93, 95% CI [-1.26, -0.61], t(488) = -5.64, p < .001; Std. beta = -1.11, 95% CI [-1.49, -0.72])
## - The effect of HMPbodysubsite [Saliva] is statistically significant and positive (beta = 0.92, 95% CI [0.62, 1.22], t(488) = 6.01, p < .001; Std. beta = 1.09, 95% CI [0.73, 1.45])
## - The effect of HMPbodysubsite [Stool] is statistically significant and positive (beta = 0.42, 95% CI [0.11, 0.74], t(488) = 2.65, p = 0.008; Std. beta = 0.50, 95% CI [0.13, 0.87])
## - The effect of HMPbodysubsite [Subgingival plaque] is statistically significant and positive (beta = 0.93, 95% CI [0.63, 1.23], t(488) = 6.06, p < .001; Std. beta = 1.10, 95% CI [0.74, 1.46])
## - The effect of HMPbodysubsite [Supragingival plaque] is statistically significant and positive (beta = 0.92, 95% CI [0.61, 1.23], t(488) = 5.84, p < .001; Std. beta = 1.09, 95% CI [0.73, 1.46])
## - The effect of HMPbodysubsite [Throat] is statistically significant and positive (beta = 0.52, 95% CI [0.22, 0.82], t(488) = 3.37, p < .001; Std. beta = 0.62, 95% CI [0.26, 0.98])
## - The effect of HMPbodysubsite [Tongue dorsum] is statistically non-significant and positive (beta = 0.19, 95% CI [-0.12, 0.50], t(488) = 1.21, p = 0.228; Std. beta = 0.23, 95% CI [-0.14, 0.59])
## - The effect of HMPbodysubsite [Vaginal introitus] is statistically significant and negative (beta = -1.28, 95% CI [-1.60, -0.97], t(488) = -8.04, p < .001; Std. beta = -1.52, 95% CI [-1.89, -1.15])
## - The interaction effect of HMPbodysubsite [Attached Keratinized gingiva] on sex [male] is statistically non-significant and positive (beta = 0.16, 95% CI [-0.27, 0.59], t(488) = 0.74, p = 0.460; Std. beta = 0.19, 95% CI [-0.32, 0.70])
## - The interaction effect of HMPbodysubsite [Buccal mucosa] on sex [male] is statistically non-significant and positive (beta = 0.34, 95% CI [-0.10, 0.77], t(488) = 1.51, p = 0.132; Std. beta = 0.40, 95% CI [-0.12, 0.92])
## - The interaction effect of HMPbodysubsite [Hard palate] on sex [male] is statistically significant and positive (beta = 0.69, 95% CI [0.25, 1.13], t(488) = 3.06, p = 0.002; Std. beta = 0.82, 95% CI [0.29, 1.34])
## - The interaction effect of HMPbodysubsite [Left Retroauricular crease] on sex [male] is statistically non-significant and positive (beta = 0.11, 95% CI [-0.39, 0.60], t(488) = 0.43, p = 0.665; Std. beta = 0.13, 95% CI [-0.46, 0.72])
## - The interaction effect of HMPbodysubsite [Mid vagina] on sex [male] is statistically non-significant and negative (beta = -0.14, 95% CI [-0.55, 0.28], t(488) = -0.65, p = 0.519; Std. beta = -0.16, 95% CI [-0.66, 0.33])
## - The interaction effect of HMPbodysubsite [Palatine Tonsils] on sex [male] is statistically non-significant and negative (beta = -0.13, 95% CI [-0.61, 0.34], t(488) = -0.55, p = 0.579; Std. beta = -0.16, 95% CI [-0.72, 0.40])
## - The interaction effect of HMPbodysubsite [Posterior fornix] on sex [male] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.39, 0.44], t(488) = 0.13, p = 0.900; Std. beta = 0.03, 95% CI [-0.46, 0.53])
## - The interaction effect of HMPbodysubsite [Right Retroauricular crease] on sex [male] is statistically non-significant and positive (beta = 0.13, 95% CI [-0.30, 0.56], t(488) = 0.60, p = 0.550; Std. beta = 0.16, 95% CI [-0.36, 0.67])
## - The interaction effect of HMPbodysubsite [Saliva] on sex [male] is statistically non-significant and negative (beta = -0.16, 95% CI [-0.58, 0.26], t(488) = -0.76, p = 0.447; Std. beta = -0.19, 95% CI [-0.69, 0.30])
## - The interaction effect of HMPbodysubsite [Stool] on sex [male] is statistically non-significant and negative (beta = -0.09, 95% CI [-0.52, 0.33], t(488) = -0.42, p = 0.671; Std. beta = -0.11, 95% CI [-0.61, 0.39])
## - The interaction effect of HMPbodysubsite [Subgingival plaque] on sex [male] is statistically non-significant and positive (beta = 0.10, 95% CI [-0.32, 0.52], t(488) = 0.46, p = 0.642; Std. beta = 0.12, 95% CI [-0.38, 0.62])
## - The interaction effect of HMPbodysubsite [Supragingival plaque] on sex [male] is statistically non-significant and positive (beta = 0.25, 95% CI [-0.18, 0.67], t(488) = 1.14, p = 0.255; Std. beta = 0.29, 95% CI [-0.21, 0.80])
## - The interaction effect of HMPbodysubsite [Tongue dorsum] on sex [male] is statistically non-significant and positive (beta = 0.05, 95% CI [-0.29, 0.38], t(488) = 0.26, p = 0.792; Std. beta = 0.05, 95% CI [-0.34, 0.45])
## - The interaction effect of HMPbodysubsite [Vaginal introitus] on sex [male] is statistically significant and negative (beta = -0.51, 95% CI [-0.82, -0.20], t(488) = -3.25, p = 0.001; Std. beta = -0.60, 95% CI [-0.97, -0.24])
##
## Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using the Wald approximation.## The ANOVA suggests that:
##
## - The main effect of sex is statistically significant and small (F(1, 488) = 12.31, p < .001; Eta2 (partial) = 0.02, 95% CI [6.98e-03, 1.00])
## - The main effect of HMPbodysubsite is statistically significant and large (F(15, 488) = 96.72, p < .001; Eta2 (partial) = 0.75, 95% CI [0.72, 1.00])
## - The interaction between sex and HMPbodysubsite is statistically significant and medium (F(12, 488) = 2.74, p = 0.001; Eta2 (partial) = 0.06, 95% CI [0.01, 1.00])
##
## Effect sizes were labelled following Field's (2013) recommendations.8.2 Simpson
## Anova Table (Type II tests)
##
## Response: Alpha.Score
## Sum Sq Df F value Pr(>F)
## sex 0.00170 1 2.1934 0.1393
## HMPbodysubsite 0.72782 15 62.5740 <2e-16 ***
## sex:HMPbodysubsite 0.00851 12 0.9150 0.5315
## Residuals 0.37143 479
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## We fitted a linear model (estimated using OLS) to predict Alpha.Score with sex and HMPbodysubsite (formula: Alpha.Score ~ sex * HMPbodysubsite). The model explains a statistically significant and substantial proportion of variance (R2 = 0.68, F(28, 479) = 35.74, p < .001, adj. R2 = 0.66). The model's intercept, corresponding to sex = female and HMPbodysubsite = Anterior_nares, is at 0.96 (95% CI [0.95, 0.98], t(479) = 119.76, p < .001). Within this model:
##
## - The effect of sex [male] is statistically non-significant and positive (beta = 0.01, 95% CI [-0.01, 0.03], t(479) = 1.00, p = 0.320; Std. beta = 0.23, 95% CI [-0.23, 0.69])
## - The effect of HMPbodysubsite [Attached Keratinized gingiva] is statistically significant and negative (beta = -0.02, 95% CI [-0.04, -2.78e-03], t(479) = -2.24, p = 0.025; Std. beta = -0.47, 95% CI [-0.88, -0.06])
## - The effect of HMPbodysubsite [Buccal mucosa] is statistically significant and negative (beta = -0.04, 95% CI [-0.06, -0.02], t(479) = -3.89, p < .001; Std. beta = -0.85, 95% CI [-1.28, -0.42])
## - The effect of HMPbodysubsite [Hard palate] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.03, 7.01e-03], t(479) = -1.28, p = 0.200; Std. beta = -0.28, 95% CI [-0.70, 0.15])
## - The effect of HMPbodysubsite [Left Retroauricular crease] is statistically significant and negative (beta = -0.04, 95% CI [-0.06, -0.02], t(479) = -3.47, p < .001; Std. beta = -0.79, 95% CI [-1.23, -0.34])
## - The effect of HMPbodysubsite [Mid vagina] is statistically significant and negative (beta = -0.11, 95% CI [-0.13, -0.08], t(479) = -8.63, p < .001; Std. beta = -2.31, 95% CI [-2.83, -1.78])
## - The effect of HMPbodysubsite [Palatine Tonsils] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.22e-03, 0.04], t(479) = 1.84, p = 0.066; Std. beta = 0.38, 95% CI [-0.03, 0.79])
## - The effect of HMPbodysubsite [Posterior fornix] is statistically significant and negative (beta = -0.18, 95% CI [-0.21, -0.16], t(479) = -13.92, p < .001; Std. beta = -3.87, 95% CI [-4.42, -3.33])
## - The effect of HMPbodysubsite [Right Retroauricular crease] is statistically significant and negative (beta = -0.04, 95% CI [-0.07, -0.02], t(479) = -4.12, p < .001; Std. beta = -0.93, 95% CI [-1.38, -0.49])
## - The effect of HMPbodysubsite [Saliva] is statistically significant and positive (beta = 0.03, 95% CI [6.55e-03, 0.05], t(479) = 2.63, p = 0.009; Std. beta = 0.55, 95% CI [0.14, 0.96])
## - The effect of HMPbodysubsite [Stool] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.17e-03, 0.04], t(479) = 1.85, p = 0.065; Std. beta = 0.40, 95% CI [-0.02, 0.83])
## - The effect of HMPbodysubsite [Subgingival plaque] is statistically significant and positive (beta = 0.03, 95% CI [8.72e-03, 0.05], t(479) = 2.84, p = 0.005; Std. beta = 0.59, 95% CI [0.18, 1.00])
## - The effect of HMPbodysubsite [Supragingival plaque] is statistically significant and positive (beta = 0.03, 95% CI [8.03e-03, 0.05], t(479) = 2.75, p = 0.006; Std. beta = 0.59, 95% CI [0.17, 1.02])
## - The effect of HMPbodysubsite [Throat] is statistically non-significant and positive (beta = 0.01, 95% CI [-5.30e-03, 0.03], t(479) = 1.43, p = 0.152; Std. beta = 0.30, 95% CI [-0.11, 0.71])
## - The effect of HMPbodysubsite [Tongue dorsum] is statistically non-significant and positive (beta = 1.05e-03, 95% CI [-0.02, 0.02], t(479) = 0.10, p = 0.919; Std. beta = 0.02, 95% CI [-0.40, 0.45])
## - The effect of HMPbodysubsite [Vaginal introitus] is statistically significant and negative (beta = -0.14, 95% CI [-0.16, -0.11], t(479) = -11.33, p < .001; Std. beta = -2.92, 95% CI [-3.43, -2.42])
## - The interaction effect of HMPbodysubsite [Attached Keratinized gingiva] on sex [male] is statistically non-significant and negative (beta = -8.50e-03, 95% CI [-0.04, 0.02], t(479) = -0.60, p = 0.549; Std. beta = -0.18, 95% CI [-0.76, 0.41])
## - The interaction effect of HMPbodysubsite [Buccal mucosa] on sex [male] is statistically non-significant and positive (beta = 5.67e-03, 95% CI [-0.02, 0.03], t(479) = 0.40, p = 0.692; Std. beta = 0.12, 95% CI [-0.47, 0.71])
## - The interaction effect of HMPbodysubsite [Hard palate] on sex [male] is statistically non-significant and positive (beta = 0.01, 95% CI [-0.02, 0.04], t(479) = 0.90, p = 0.369; Std. beta = 0.28, 95% CI [-0.33, 0.88])
## - The interaction effect of HMPbodysubsite [Left Retroauricular crease] on sex [male] is statistically non-significant and negative (beta = -7.27e-03, 95% CI [-0.04, 0.02], t(479) = -0.45, p = 0.653; Std. beta = -0.15, 95% CI [-0.82, 0.52])
## - The interaction effect of HMPbodysubsite [Mid vagina] on sex [male] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.04, 0.01], t(479) = -1.13, p = 0.257; Std. beta = -0.33, 95% CI [-0.91, 0.24])
## - The interaction effect of HMPbodysubsite [Palatine Tonsils] on sex [male] is statistically non-significant and negative (beta = -9.88e-03, 95% CI [-0.04, 0.02], t(479) = -0.64, p = 0.525; Std. beta = -0.21, 95% CI [-0.85, 0.43])
## - The interaction effect of HMPbodysubsite [Posterior fornix] on sex [male] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.04, 0.02], t(479) = -0.78, p = 0.438; Std. beta = -0.23, 95% CI [-0.80, 0.35])
## - The interaction effect of HMPbodysubsite [Right Retroauricular crease] on sex [male] is statistically non-significant and negative (beta = -0.02, 95% CI [-0.04, 0.01], t(479) = -1.06, p = 0.291; Std. beta = -0.32, 95% CI [-0.91, 0.27])
## - The interaction effect of HMPbodysubsite [Saliva] on sex [male] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.04, 0.01], t(479) = -1.05, p = 0.293; Std. beta = -0.31, 95% CI [-0.89, 0.27])
## - The interaction effect of HMPbodysubsite [Stool] on sex [male] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.04, 0.01], t(479) = -0.91, p = 0.362; Std. beta = -0.27, 95% CI [-0.86, 0.31])
## - The interaction effect of HMPbodysubsite [Subgingival plaque] on sex [male] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.04, 0.02], t(479) = -0.75, p = 0.454; Std. beta = -0.22, 95% CI [-0.80, 0.36])
## - The interaction effect of HMPbodysubsite [Supragingival plaque] on sex [male] is statistically non-significant and negative (beta = -1.73e-03, 95% CI [-0.03, 0.03], t(479) = -0.12, p = 0.903; Std. beta = -0.04, 95% CI [-0.62, 0.55])
## - The interaction effect of HMPbodysubsite [Tongue dorsum] on sex [male] is statistically non-significant and positive (beta = 0.01, 95% CI [-0.01, 0.03], t(479) = 1.00, p = 0.320; Std. beta = 0.23, 95% CI [-0.23, 0.69])
## - The interaction effect of HMPbodysubsite [Vaginal introitus] on sex [male] is statistically significant and negative (beta = -0.02, 95% CI [-0.04, -2.78e-03], t(479) = -2.24, p = 0.025; Std. beta = -0.47, 95% CI [-0.88, -0.06])
##
## Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using the Wald approximation.## The ANOVA suggests that:
##
## - The main effect of sex is statistically not significant and very small (F(1, 479) = 2.19, p = 0.139; Eta2 (partial) = 4.56e-03, 95% CI [0.00, 1.00])
## - The main effect of HMPbodysubsite is statistically significant and large (F(15, 479) = 62.57, p < .001; Eta2 (partial) = 0.66, 95% CI [0.62, 1.00])
## - The interaction between sex and HMPbodysubsite is statistically not significant and small (F(12, 479) = 0.92, p = 0.532; Eta2 (partial) = 0.02, 95% CI [0.00, 1.00])
##
## Effect sizes were labelled following Field's (2013) recommendations.8.3 Phylogenetic
## Anova Table (Type II tests)
##
## Response: Alpha.Score
## Sum Sq Df F value Pr(>F)
## sex 22.3 1 3.9495 0.047430 *
## HMPbodysubsite 9391.5 15 110.8586 < 2.2e-16 ***
## sex:HMPbodysubsite 172.8 12 2.5503 0.002794 **
## Residuals 2823.9 500
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## We fitted a linear model (estimated using OLS) to predict Alpha.Score with sex and HMPbodysubsite (formula: Alpha.Score ~ sex * HMPbodysubsite). The model explains a statistically significant and substantial proportion of variance (R2 = 0.78, F(28, 500) = 63.68, p < .001, adj. R2 = 0.77). The model's intercept, corresponding to sex = female and HMPbodysubsite = Anterior_nares, is at 10.15 (95% CI [8.80, 11.50], t(500) = 14.80, p < .001). Within this model:
##
## - The effect of sex [male] is statistically non-significant and negative (beta = -1.36, 95% CI [-3.26, 0.55], t(500) = -1.40, p = 0.163; Std. beta = -0.27, 95% CI [-0.66, 0.11])
## - The effect of HMPbodysubsite [Attached Keratinized gingiva] is statistically non-significant and negative (beta = -0.77, 95% CI [-2.44, 0.91], t(500) = -0.90, p = 0.368; Std. beta = -0.16, 95% CI [-0.49, 0.18])
## - The effect of HMPbodysubsite [Buccal mucosa] is statistically significant and positive (beta = 2.47, 95% CI [0.69, 4.25], t(500) = 2.72, p = 0.007; Std. beta = 0.50, 95% CI [0.14, 0.86])
## - The effect of HMPbodysubsite [Hard palate] is statistically significant and positive (beta = 4.10, 95% CI [2.36, 5.84], t(500) = 4.63, p < .001; Std. beta = 0.83, 95% CI [0.48, 1.18])
## - The effect of HMPbodysubsite [Left Retroauricular crease] is statistically significant and negative (beta = -2.96, 95% CI [-4.77, -1.15], t(500) = -3.22, p = 0.001; Std. beta = -0.60, 95% CI [-0.96, -0.23])
## - The effect of HMPbodysubsite [Mid vagina] is statistically significant and negative (beta = -2.76, 95% CI [-4.45, -1.07], t(500) = -3.20, p = 0.001; Std. beta = -0.56, 95% CI [-0.90, -0.22])
## - The effect of HMPbodysubsite [Palatine Tonsils] is statistically significant and positive (beta = 5.43, 95% CI [3.74, 7.12], t(500) = 6.32, p < .001; Std. beta = 1.10, 95% CI [0.76, 1.44])
## - The effect of HMPbodysubsite [Posterior fornix] is statistically significant and negative (beta = -4.41, 95% CI [-6.15, -2.67], t(500) = -4.98, p < .001; Std. beta = -0.89, 95% CI [-1.24, -0.54])
## - The effect of HMPbodysubsite [Right Retroauricular crease] is statistically significant and negative (beta = -3.18, 95% CI [-4.96, -1.40], t(500) = -3.51, p < .001; Std. beta = -0.64, 95% CI [-1.00, -0.28])
## - The effect of HMPbodysubsite [Saliva] is statistically significant and positive (beta = 9.40, 95% CI [7.71, 11.09], t(500) = 10.93, p < .001; Std. beta = 1.90, 95% CI [1.56, 2.24])
## - The effect of HMPbodysubsite [Stool] is statistically significant and positive (beta = 2.85, 95% CI [1.09, 4.61], t(500) = 3.18, p = 0.002; Std. beta = 0.58, 95% CI [0.22, 0.93])
## - The effect of HMPbodysubsite [Subgingival plaque] is statistically significant and positive (beta = 9.36, 95% CI [7.69, 11.04], t(500) = 10.98, p < .001; Std. beta = 1.89, 95% CI [1.56, 2.23])
## - The effect of HMPbodysubsite [Supragingival plaque] is statistically significant and positive (beta = 7.59, 95% CI [5.85, 9.33], t(500) = 8.57, p < .001; Std. beta = 1.54, 95% CI [1.18, 1.89])
## - The effect of HMPbodysubsite [Throat] is statistically significant and positive (beta = 4.98, 95% CI [3.31, 6.66], t(500) = 5.84, p < .001; Std. beta = 1.01, 95% CI [0.67, 1.35])
## - The effect of HMPbodysubsite [Tongue dorsum] is statistically significant and positive (beta = 2.91, 95% CI [1.19, 4.63], t(500) = 3.32, p < .001; Std. beta = 0.59, 95% CI [0.24, 0.94])
## - The effect of HMPbodysubsite [Vaginal introitus] is statistically significant and negative (beta = -2.23, 95% CI [-3.94, -0.53], t(500) = -2.57, p = 0.010; Std. beta = -0.45, 95% CI [-0.80, -0.11])
## - The interaction effect of HMPbodysubsite [Attached Keratinized gingiva] on sex [male] is statistically non-significant and positive (beta = 1.51, 95% CI [-0.88, 3.90], t(500) = 1.24, p = 0.217; Std. beta = 0.30, 95% CI [-0.18, 0.79])
## - The interaction effect of HMPbodysubsite [Buccal mucosa] on sex [male] is statistically significant and positive (beta = 3.56, 95% CI [1.10, 6.03], t(500) = 2.84, p = 0.005; Std. beta = 0.72, 95% CI [0.22, 1.22])
## - The interaction effect of HMPbodysubsite [Hard palate] on sex [male] is statistically significant and positive (beta = 3.08, 95% CI [0.57, 5.59], t(500) = 2.41, p = 0.016; Std. beta = 0.62, 95% CI [0.12, 1.13])
## - The interaction effect of HMPbodysubsite [Left Retroauricular crease] on sex [male] is statistically non-significant and positive (beta = 1.12, 95% CI [-1.57, 3.82], t(500) = 0.82, p = 0.413; Std. beta = 0.23, 95% CI [-0.32, 0.77])
## - The interaction effect of HMPbodysubsite [Mid vagina] on sex [male] is statistically non-significant and positive (beta = 1.32, 95% CI [-1.10, 3.73], t(500) = 1.07, p = 0.284; Std. beta = 0.27, 95% CI [-0.22, 0.75])
## - The interaction effect of HMPbodysubsite [Palatine Tonsils] on sex [male] is statistically non-significant and positive (beta = 1.21, 95% CI [-1.37, 3.80], t(500) = 0.92, p = 0.356; Std. beta = 0.25, 95% CI [-0.28, 0.77])
## - The interaction effect of HMPbodysubsite [Posterior fornix] on sex [male] is statistically non-significant and positive (beta = 2.02, 95% CI [-0.38, 4.42], t(500) = 1.65, p = 0.099; Std. beta = 0.41, 95% CI [-0.08, 0.89])
## - The interaction effect of HMPbodysubsite [Right Retroauricular crease] on sex [male] is statistically non-significant and positive (beta = 1.69, 95% CI [-0.76, 4.14], t(500) = 1.35, p = 0.177; Std. beta = 0.34, 95% CI [-0.15, 0.84])
## - The interaction effect of HMPbodysubsite [Saliva] on sex [male] is statistically non-significant and negative (beta = -0.25, 95% CI [-2.63, 2.13], t(500) = -0.21, p = 0.835; Std. beta = -0.05, 95% CI [-0.53, 0.43])
## - The interaction effect of HMPbodysubsite [Stool] on sex [male] is statistically non-significant and positive (beta = 0.90, 95% CI [-1.53, 3.32], t(500) = 0.73, p = 0.467; Std. beta = 0.18, 95% CI [-0.31, 0.67])
## - The interaction effect of HMPbodysubsite [Subgingival plaque] on sex [male] is statistically significant and positive (beta = 3.84, 95% CI [1.44, 6.24], t(500) = 3.14, p = 0.002; Std. beta = 0.78, 95% CI [0.29, 1.26])
## - The interaction effect of HMPbodysubsite [Supragingival plaque] on sex [male] is statistically significant and positive (beta = 2.68, 95% CI [0.27, 5.09], t(500) = 2.18, p = 0.029; Std. beta = 0.54, 95% CI [0.05, 1.03])
## - The interaction effect of HMPbodysubsite [Tongue dorsum] on sex [male] is statistically non-significant and negative (beta = -1.36, 95% CI [-3.26, 0.55], t(500) = -1.40, p = 0.163; Std. beta = -0.27, 95% CI [-0.66, 0.11])
## - The interaction effect of HMPbodysubsite [Vaginal introitus] on sex [male] is statistically non-significant and negative (beta = -0.77, 95% CI [-2.44, 0.91], t(500) = -0.90, p = 0.368; Std. beta = -0.16, 95% CI [-0.49, 0.18])
##
## Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using the Wald approximation.## The ANOVA suggests that:
##
## - The main effect of sex is statistically significant and very small (F(1, 500) = 3.95, p = 0.047; Eta2 (partial) = 7.84e-03, 95% CI [4.65e-05, 1.00])
## - The main effect of HMPbodysubsite is statistically significant and large (F(15, 500) = 110.86, p < .001; Eta2 (partial) = 0.77, 95% CI [0.74, 1.00])
## - The interaction between sex and HMPbodysubsite is statistically significant and small (F(12, 500) = 2.55, p = 0.003; Eta2 (partial) = 0.06, 95% CI [0.01, 1.00])
##
## Effect sizes were labelled following Field's (2013) recommendations.8.4 Richness
## Anova Table (Type II tests)
##
## Response: Alpha.Score
## Sum Sq Df F value Pr(>F)
## sex 57658 1 20.181 8.752e-06 ***
## HMPbodysubsite 3907814 15 91.185 < 2.2e-16 ***
## sex:HMPbodysubsite 70147 12 2.046 0.01906 *
## Residuals 1434248 502
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## We fitted a linear model (estimated using OLS) to predict Alpha.Score with sex and HMPbodysubsite (formula: Alpha.Score ~ sex * HMPbodysubsite). The model explains a statistically significant and substantial proportion of variance (R2 = 0.75, F(28, 502) = 54.89, p < .001, adj. R2 = 0.74). The model's intercept, corresponding to sex = female and HMPbodysubsite = Anterior_nares, is at 254.36 (95% CI [222.70, 286.03], t(502) = 15.78, p < .001). Within this model:
##
## - The effect of sex [male] is statistically non-significant and positive (beta = 3.79, 95% CI [-39.23, 46.81], t(502) = 0.17, p = 0.863; Std. beta = 0.04, 95% CI [-0.37, 0.45])
## - The effect of HMPbodysubsite [Attached Keratinized gingiva] is statistically non-significant and negative (beta = -19.36, 95% CI [-58.14, 19.42], t(502) = -0.98, p = 0.327; Std. beta = -0.18, 95% CI [-0.55, 0.19])
## - The effect of HMPbodysubsite [Buccal mucosa] is statistically non-significant and negative (beta = -0.68, 95% CI [-41.81, 40.46], t(502) = -0.03, p = 0.974; Std. beta = -6.45e-03, 95% CI [-0.40, 0.39])
## - The effect of HMPbodysubsite [Hard palate] is statistically non-significant and positive (beta = 32.40, 95% CI [-8.24, 73.04], t(502) = 1.57, p = 0.118; Std. beta = 0.31, 95% CI [-0.08, 0.70])
## - The effect of HMPbodysubsite [Left Retroauricular crease] is statistically significant and negative (beta = -92.16, 95% CI [-133.85, -50.48], t(502) = -4.34, p < .001; Std. beta = -0.88, 95% CI [-1.28, -0.48])
## - The effect of HMPbodysubsite [Mid vagina] is statistically significant and negative (beta = -88.91, 95% CI [-127.69, -50.13], t(502) = -4.50, p < .001; Std. beta = -0.85, 95% CI [-1.22, -0.48])
## - The effect of HMPbodysubsite [Palatine Tonsils] is statistically significant and positive (beta = 107.49, 95% CI [68.41, 146.58], t(502) = 5.40, p < .001; Std. beta = 1.03, 95% CI [0.65, 1.40])
## - The effect of HMPbodysubsite [Posterior fornix] is statistically significant and negative (beta = -107.09, 95% CI [-147.28, -66.90], t(502) = -5.23, p < .001; Std. beta = -1.02, 95% CI [-1.40, -0.64])
## - The effect of HMPbodysubsite [Right Retroauricular crease] is statistically significant and negative (beta = -76.13, 95% CI [-116.76, -35.49], t(502) = -3.68, p < .001; Std. beta = -0.73, 95% CI [-1.11, -0.34])
## - The effect of HMPbodysubsite [Saliva] is statistically significant and positive (beta = 175.97, 95% CI [136.88, 215.06], t(502) = 8.85, p < .001; Std. beta = 1.68, 95% CI [1.31, 2.05])
## - The effect of HMPbodysubsite [Stool] is statistically significant and positive (beta = 54.53, 95% CI [14.33, 94.72], t(502) = 2.67, p = 0.008; Std. beta = 0.52, 95% CI [0.14, 0.90])
## - The effect of HMPbodysubsite [Subgingival plaque] is statistically significant and positive (beta = 147.38, 95% CI [108.88, 185.87], t(502) = 7.52, p < .001; Std. beta = 1.41, 95% CI [1.04, 1.77])
## - The effect of HMPbodysubsite [Supragingival plaque] is statistically significant and positive (beta = 146.53, 95% CI [106.74, 186.32], t(502) = 7.24, p < .001; Std. beta = 1.40, 95% CI [1.02, 1.78])
## - The effect of HMPbodysubsite [Throat] is statistically significant and positive (beta = 108.00, 95% CI [69.22, 146.78], t(502) = 5.47, p < .001; Std. beta = 1.03, 95% CI [0.66, 1.40])
## - The effect of HMPbodysubsite [Tongue dorsum] is statistically significant and positive (beta = 53.69, 95% CI [13.90, 93.48], t(502) = 2.65, p = 0.008; Std. beta = 0.51, 95% CI [0.13, 0.89])
## - The effect of HMPbodysubsite [Vaginal introitus] is statistically significant and negative (beta = -86.41, 95% CI [-125.50, -47.32], t(502) = -4.34, p < .001; Std. beta = -0.82, 95% CI [-1.20, -0.45])
## - The interaction effect of HMPbodysubsite [Attached Keratinized gingiva] on sex [male] is statistically non-significant and positive (beta = 14.59, 95% CI [-39.05, 68.23], t(502) = 0.53, p = 0.593; Std. beta = 0.14, 95% CI [-0.37, 0.65])
## - The interaction effect of HMPbodysubsite [Buccal mucosa] on sex [male] is statistically non-significant and positive (beta = 54.27, 95% CI [-1.33, 109.87], t(502) = 1.92, p = 0.056; Std. beta = 0.52, 95% CI [-0.01, 1.05])
## - The interaction effect of HMPbodysubsite [Hard palate] on sex [male] is statistically significant and positive (beta = 78.83, 95% CI [20.97, 136.69], t(502) = 2.68, p = 0.008; Std. beta = 0.75, 95% CI [0.20, 1.30])
## - The interaction effect of HMPbodysubsite [Left Retroauricular crease] on sex [male] is statistically non-significant and positive (beta = 26.41, 95% CI [-34.33, 87.15], t(502) = 0.85, p = 0.393; Std. beta = 0.25, 95% CI [-0.33, 0.83])
## - The interaction effect of HMPbodysubsite [Mid vagina] on sex [male] is statistically non-significant and negative (beta = -2.55, 95% CI [-56.42, 51.31], t(502) = -0.09, p = 0.926; Std. beta = -0.02, 95% CI [-0.54, 0.49])
## - The interaction effect of HMPbodysubsite [Palatine Tonsils] on sex [male] is statistically non-significant and positive (beta = 0.67, 95% CI [-57.20, 58.53], t(502) = 0.02, p = 0.982; Std. beta = 6.36e-03, 95% CI [-0.55, 0.56])
## - The interaction effect of HMPbodysubsite [Posterior fornix] on sex [male] is statistically non-significant and positive (beta = 8.93, 95% CI [-45.18, 63.03], t(502) = 0.32, p = 0.746; Std. beta = 0.09, 95% CI [-0.43, 0.60])
## - The interaction effect of HMPbodysubsite [Right Retroauricular crease] on sex [male] is statistically non-significant and positive (beta = 17.38, 95% CI [-38.41, 73.17], t(502) = 0.61, p = 0.541; Std. beta = 0.17, 95% CI [-0.37, 0.70])
## - The interaction effect of HMPbodysubsite [Saliva] on sex [male] is statistically non-significant and negative (beta = -12.91, 95% CI [-66.35, 40.53], t(502) = -0.47, p = 0.635; Std. beta = -0.12, 95% CI [-0.63, 0.39])
## - The interaction effect of HMPbodysubsite [Stool] on sex [male] is statistically non-significant and negative (beta = -2.59, 95% CI [-56.96, 51.78], t(502) = -0.09, p = 0.925; Std. beta = -0.02, 95% CI [-0.54, 0.49])
## - The interaction effect of HMPbodysubsite [Subgingival plaque] on sex [male] is statistically non-significant and positive (beta = 35.48, 95% CI [-18.68, 89.63], t(502) = 1.29, p = 0.199; Std. beta = 0.34, 95% CI [-0.18, 0.85])
## - The interaction effect of HMPbodysubsite [Supragingival plaque] on sex [male] is statistically non-significant and positive (beta = 36.71, 95% CI [-17.91, 91.32], t(502) = 1.32, p = 0.187; Std. beta = 0.35, 95% CI [-0.17, 0.87])
## - The interaction effect of HMPbodysubsite [Tongue dorsum] on sex [male] is statistically non-significant and positive (beta = 3.79, 95% CI [-39.23, 46.81], t(502) = 0.17, p = 0.863; Std. beta = 0.04, 95% CI [-0.37, 0.45])
## - The interaction effect of HMPbodysubsite [Vaginal introitus] on sex [male] is statistically non-significant and negative (beta = -19.36, 95% CI [-58.14, 19.42], t(502) = -0.98, p = 0.327; Std. beta = -0.18, 95% CI [-0.55, 0.19])
##
## Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using the Wald approximation.## The ANOVA suggests that:
##
## - The main effect of sex is statistically significant and small (F(1, 502) = 20.18, p < .001; Eta2 (partial) = 0.04, 95% CI [0.02, 1.00])
## - The main effect of HMPbodysubsite is statistically significant and large (F(15, 502) = 91.18, p < .001; Eta2 (partial) = 0.73, 95% CI [0.70, 1.00])
## - The interaction between sex and HMPbodysubsite is statistically significant and small (F(12, 502) = 2.05, p = 0.019; Eta2 (partial) = 0.05, 95% CI [3.82e-03, 1.00])
##
## Effect sizes were labelled following Field's (2013) recommendations.9 Plots
ps.list[["RAR"]][["Plots"]] <- list()
ps.list[["RAR"]][["Plots"]] <- lapply(names(methods.alpha), function(alpha){
tmp.data <- na.omit(as.data.frame(caseInfStats[["dataFort.ref"]][[alpha]]) )
ggplot(tmp.data, aes(x = HMPbodysubsite, y=Alpha.Score)) +
geom_boxplot(aes(fill = HMPbodysubsite)) +
ggbeeswarm::geom_quasirandom(size = 0.75) + # spaces the dots out nicely
facet_grid(. ~ .) + # (Y-axis ~ X-axis)
theme(legend.position = "none",
axis.text.x = element_text(angle = 33, hjust = 1, vjust=1)
) +
labs(
title = "Diversity Scores by Body Sub-Site",
# caption = "",
y = paste0("Diversity (", alpha,")"),
x = "Body Sub-Site"
)
})
names(ps.list[["RAR"]][["Plots"]]) <- names(methods.alpha)
ps.list[["RAR"]][["Plots"]]## $Shannon
##
## $Simpson
##
## $Phylogenetic
##
## $Richness